Project Grant 2611926
Award Date 8/1/26
Completion Date 7/31/29
Dollars Obligated $335K
Federal Agency
Federal Grant Program
Assistance Type
Project Grant
Place of Performance
Madison, WI 53715, USA
Similar Awards
- The National Science Foundation Division of Computing and Communication Foundations awarded The University of Chicago $330,438 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop a unified theory of information-computation tradeoffs for statistical tasks. The project establishes lower bounds in restricted but broad computational models, including low-degree polynomials, statistical queries, polynomial threshold functions, and the...
- The National Science Foundation Division of Computing and Communication Foundations awarded the University of Wisconsin - Madison $451,577 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop approximate Bayesian inference methods for diffusion posteriors in generative artificial intelligence. The project addresses a gap in current generative models used for scientific applications: while these models can produce realistic outputs, they...
- The National Science Foundation Division of Computing and Communication Foundations awarded the University of Wisconsin–Madison $352,098 on January 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop methods ensuring deep-learning models for computational imaging remain robust and accurate when data conditions shift between training and test environments. The research addresses a critical gap in current computational imaging systems, which...
- The National Science Foundation Division of Computing and Communication Foundations awarded the University of Wisconsin - Madison $249,999 on August 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to develop graph-centric multi-agent systems powered by large language models. The project develops new graph-based methods for designing, executing, and adapting multi-agent artificial intelligence systems in which multiple agents communicate and collaborate...
- The National Science Foundation Division of Mathematical Sciences awarded the University of Wisconsin - Madison $179,999 on July 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop mathematical theories for machine learning algorithms that balance statistical accuracy, privacy guarantees, and computational scalability in high-dimensional settings. The project investigates fundamental trade-offs between accuracy, privacy, and computational efficiency in AI...
- The National Science Foundation Division of Mathematical Sciences awarded the University of Wisconsin–Madison $241,200 on August 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop novel statistical learning and data embedding tools using spectral techniques rooted in matrix factorizations, truncations, and perturbations, with emphasis on robustness, inference, and modeling. The research program spans methodology, theory, and applications with interdisciplinary...
- The National Science Foundation Division of Mathematical Sciences awarded the University of Wisconsin–Madison $250,000 on July 1, 2026, for statistical research on reliable estimation, prediction, and causal inference with AI-generated synthetic datasets under the Mathematical and Physical Sciences program (CFDA 47.049). The project develops statistical foundations and a unified theory for integrating multiple heterogeneous AI-generated synthetic datasets into scientific analysis while...
- The National Science Foundation Division of Mathematical Sciences awarded the University of Wisconsin–Madison $309,038 on September 1, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop a unified mathematical framework connecting random matrices with prescribed margins, Schrödinger bridges, and optimal transport theory, with applications to generative AI for multimodal data. The project addresses the problem of inferring missing structure in systems where...
- The National Science Foundation Division of Computing and Communication Foundations awarded the University of Massachusetts $375,000 on September 1, 2026, under the Computer and Information Science and Engineering program (CFDA 47.070) to advance fine-grained complexity theory for matrix computations. The project seeks to understand which matrix computation problems admit further algorithmic improvements and what techniques will unlock them. Research will apply fine-grained complexity theory...
- The National Science Foundation Division of Mathematical Sciences awarded the University of Wisconsin–Madison $180,000 on July 15, 2026, under the Mathematical and Physical Sciences program (CFDA 47.049) to develop fast, flexible, and accurate covariance models for Gaussian processes in machine learning and artificial intelligence applications. The project addresses computational and methodological challenges in scaling Gaussian process models to large, high-resolution datasets by exploiting...